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Metronomic chemotherapy plus anti-PD-1 in metastatic breast cancer: a Bayesian adaptive randomized phase 2 trial

Nature Medicine (2024)Cite this article

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Abstract

It remains unclear whether metronomic chemotherapy is superior to conventional chemotherapy when combined with immune checkpoint blockade. Here we performed a phase 2 clinical trial of metronomic chemotherapy combined with PD-1 blockade to compare the efficacy of combined conventional chemotherapy and PD-1 blockade using Bayesian adaptive randomization and efficacy monitoring. Eligible patients had metastatic HER2-negative breast cancer and had not received more than one prior line of standard chemotherapy. Patients (total n = 97) were randomized to receive (1) metronomic vinorelbine (NVB) monotherapy (n = 11), (2) NVB plus anti-PD-1 toripalimab (n = 7), (3) anti-angiogenic bevacizumab, NVB and toripalimab (n = 27), (4) conventional cisplatin, NVB and toripalimab (n = 26), or (5) metronomic cyclophosphamide, capecitabine, NVB and toripalimab (the VEX cohort) (n = 26). The primary endpoint was disease control rate (DCR). Secondary objectives included progression-free survival (PFS) and safety. The study met the primary endpoint. The VEX (69.7%) and cisplatin (73.7%) cohorts had the highest DCR. The median PFS of patients in the VEX cohort was the longest, reaching 6.6 months, followed by the bevacizumab (4.0 months) and cisplatin (3.5 months) cohorts. In general, the five regimens were well tolerated, with nausea and neutropenia being the most common adverse events. An exploratory mass cytometry analysis indicated that metronomic VEX chemotherapy reprograms the systemic immune response. Together, the clinical and translational data of this study indicate that metronomic VEX chemotherapy combined with PD-1 blockade can be a treatment option in patients with breast cancer. ClinicalTrials.gov Identifier: NCT04389073.

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Fig. 1: Trial design.
Fig. 2: Anti-tumor activity after treatment in the five cohorts.
Fig. 3: Subgroup analysis according to the clinical characteristics of the patients.
Fig. 4: Metronomic VEX chemotherapy specifically reprograms systemic immune characteristics.

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Data availability

Complete de-identified patient data will be available indefinitely within 2 years of the patients’ last survival follow-up visit and will be uploaded to ClinicalTrials.gov. Single-cell sequencing data can be obtained from the Gene Expression Omnibus with accession number GSE169246. The data of human reference genome 19 can be downloaded from UCSC Xena. Any additional information required to reanalyze the data reported in this paper is available from the corresponding author upon request, with detailed proposals for the use of the information. In response to the inquiry, please be informed that the timeframe for responding to requests is approximately 2 weeks.

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Acknowledgements

We thank the patients, their families and the personnel involved in this trial. We thank Y. Yuan for his assistance with statistical analysis. This work was supported by the CAMS Innovation Fund for Medical Sciences (CIFMS 2021-I2M-1-014 to B.X. and CIFMS 2022-I2M-C&T-B-067 to H.M.), the National Natural Science Foundation of China (82230058 to F.M.) and the Beijing Hope Run Special Fund of Cancer Foundation of China (LC2021A08 to H.M.).

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Authors and Affiliations

  1. Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Hongnan Mo, Hewei Ge, Xiuwen Guan, Jingtong Zhai, Yuhan Wei, Binghe Xu & Fei Ma

  2. State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

    Hongnan Mo, Haili Qian, Binghe Xu & Fei Ma

  3. Department of Biostatistics, Peking University Clinical Research Institute, Beijing, China

    Yongpei Yu, Lanlan Yu & Xiaoyan Yan

  4. Department of Medical Oncology, Cancer Hospital of HuanXing ChaoYang District, Beijing, China

    Xiaoying Sun, Aihua Zhu & Jinjing Wang

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Contributions

H.M., Y.Y., H.G., L.Y., Y.W. and J.Z. participated in the design, execution and/or interpretation of the reported experiments or results. H.M., Y.Y., H.G., X.S., A.Z., J.W., X.G., L.Y., J.Z. and Y.W. participated in the sample acquisition or data analysis. H.M., Y.Y. and H.G. drafted the paper, with all authors contributing to the writing and providing feedback. F.M., B.X., X.Y. and H.Q. supervised all aspects of the research.

Corresponding authors

Correspondence to Haili Qian, Binghe Xu or Fei Ma.

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X.B. reports personal advisory fees from Novartis and personal payment or honoraria fees for lecture from AstraZeneca, Pfizer, Roche and Eisai, outside of the submitted work. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Clinical efficacy in patients receiving metronomic vinorelbine with or without PD-1 blockade.

Histograms showing the final probability distributions for the disease control rate (DCR) (a) and objective response rate (ORR) (b) as well as the Kaplan–Meier estimates of progression-free survival (PFS) (c) and overall survival (OS) (d). a, Among the patients receiving PD-1 blockade therapy, 54 achieved a controlled disease (DCR of 62.9%; 95% CI 52.5–72.7%), which compared favorably with the controlled DCR of 35.5% (95% CI 10.6–63.2%) in the NVB monotherapy cohort. b, ORR was 11.3% (95% CI 5.4–18.5%) in patients receiving PD-1 blockade therapy and 0% in the controlled NVB monotherapy cohort. c, Median PFS was 4.2 months (95% CI 3.2–5.3) in patients receiving PD-1 blockade therapy. In patients receiving metronomic chemotherapy with NVB alone, the median PFS was 1.4 months (95% CI 0.69–2.4). d, Median OS was 29.2 months (95% CI 19.9–41.7) in patients who received PD-1 blockade and 19.1 months (95% CI 6.6-47.2) in the control group.

Extended Data Fig. 2 Bayesian estimates of the disease control rate (DCR) according to the molecular subtype of patient, number of previous treatment lines, and presence of visceral metastasis.

Data are presented as the Bayesian estimates of DCR and 95% credible interval. TNBC, triple-negative breast cancer.

Extended Data Fig. 3 Specific reprogramming of systemic immune components is key to the efficacy of immunotherapy.

a, The t-distributed stochastic neighbor embedding (t-SNE) plots of immune cells sampled from patients receiving PD-1 blockade therapy, colored by major immune cell subsets. b, Heatmap displaying the median antigen intensity of markers used to generate a. c, Histograms of samples from baseline. None of the 32 CD45+ cell subsets was considerably different between responders (Pre-R) and nonresponders (Pre-NR). d, Principal component analysis (PCA) of samples before (Pre)and after treatment (Post). The combination therapy caused dramatic changes in the systemic immune profiles of patients. e, Comparison of the percentages of 32 identified cell subsets across the response group. f, Differential CTLA4 expression on T-cell subsets between responders (R) and nonresponders (NR). g, Differential expression of CD206 and CD33 on monocytes across the response group. In e and g, n=37 in Pre-R, n=20 in Pre-NR, n=35 in Post-R, n=22 in Post-NR. In e and g, exact P values by t- test (two-sided): *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. In e and g, boxes indicate median ± interquartile range; whiskers show minima and maxima.

Extended Data Fig. 4 Differential expression of cell markers according to the response groups.

a, Clusters 05, 30, and 31 were mainly from peripheral blood mononuclear cells (PBMCs) after treatment, whereas Clusters 03, 21, and 32 were primarily from baseline samples. b, RNA sequencing of baseline tumor tissues revealed that the infiltration of 28 immune cells in the tumor microenvironment did not correlate with immunotherapy efficacy (n=24 in R, n=14 in NR). c, PD-L1 expression (n=7 in R, n=5 in NR) and tumor mutation burden (n=12 in R, n=7 in NR) from baseline tumor samples showed no important difference between responders (R) and nonresponders (NR). Exact P values by two-sided Mann–Whitney test. d, Single-cell RNA sequencing of PBMCs from baseline samples did not show correlation between the subsets of PBMCs and the efficacy of immunotherapy (n=4 in R, n=7 in NR). e, Differences in subpopulation proportions and protein expression of T-cell subset clusters 03 and 05 between responders (R) and nonresponders (NR). f, Differences in subpopulation proportions and protein expression of monocytes Cluster 29 and Cluster 30 between responders (R) and nonresponders (NR). g, Differential expression of NK cell markers according to the response groups. In e-g, n=37 in Pre-R, n=20 in Pre-NR, n=35 in Post-R, n=22 in Post-NR. In e and f, representative histograms showing differentially expressed markers on cell subsets. In e, f and g, exact P values by t- test (two-sided): *P < 0.05, **P < 0.01. In b-d and f-g, boxes indicate median ± interquartile range; whiskers show minima and maxima.

Extended Data Fig. 5 Differential expression of cell markers according to the treatment cohorts.

a, Cells were consistently distributed across all major immune subsets at baseline. b, A consistently increase in the proportion of Cluster 04 and Cluster 14 was observed in all three cohorts. c, Differential expression of CCR7 on T-cell subsets in different treatment cohorts. d, Differential expression of the monocyte markers CD206 and CD14 after different treatments. B cell (e) and dendritic cell subsets (f) in patients did not change substantially after treatment. In b-f, n=17 in Pre-DDP, n=19 in Post-DDP; n=15 in Pre-BEV, n=16 in Post- BEV; n=25 in Pre-VEX, n=22 in Post-VEX. In b - d, exact P values by t- test (two-sided): *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001. In b-f, boxes indicate median ± interquartile range; whiskers show minima and maxima.

Extended Data Fig. 6 Cell–cell communication between the peripheral blood mononuclear cell (PBMC) subsets.

a, Circos plots showing the multiple correlation matrix between the PBMC subset frequencies in CyTOF. b, Single-cell RNA sequencing analysis verified the negative correlation between monocytes and T-cell subsets. c, Analysis of cell–cell communication between T-cell subsets and monocytes. d, Analysis of cell–cell communication between monocytes and T-cell subsets. e, Difference of cell–cell communication between responders and nonresponders. In c-e, dot color reflects communication probabilities and dot size represents computed P values (one-sided permutation test) for interactions.

Extended Data Table 1 Probability of superiority among the five cohorts in all patients
Full size table
Extended Data Table 2 Probability of superiority in the PD-1 antibody combined group
Full size table
Extended Data Table 3 Probability of superiority among the five cohorts in subgroups
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Extended Data Table 4 AEs
Full size table

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Mo, H., Yu, Y., Sun, X. et al. Metronomic chemotherapy plus anti-PD-1 in metastatic breast cancer: a Bayesian adaptive randomized phase 2 trial. Nat Med (2024). https://doi.org/10.1038/s41591-024-03088-2

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